Two-Dimensional, Two-Layer Quality Regression Model Based Batch Process Monitoring

Processes

Xin Huang¹  Luping Zhao¹ 

[1] College of Information Science and Engineering, Northeastern University, Shenyang 110819, China;

关键词: batch process;    partial least squares;    multi-phase;    multi-mode;    process monitoring;   

DOI  :  10.3390/pr10010043

来源: DOAJ

【 摘 要 】

In this paper, a two-dimensional, two-layer quality regression model is established to monitor multi-phase, multi-mode batch processes. Firstly, aiming at the multi-phase problem and the multi-mode problem simultaneously, the relations among modes and phases are captured through the analysis between process variables and quality variables by establishing a two-dimensional, two-layer regression partial least squares (PLS) model. The two-dimensional regression traces the intra-batch and inter-batch characteristics, while the two-layer structure establishes the relationship between the target process and historical modes and phases. Consequently, online monitoring is carried out for multi-phase, multi-mode batch processes based on quality prediction. In addition, the online quality prediction and monitoring results based on the proposed method and those based on the traditional phase mean PLS method are compared to prove the effectiveness of the proposed method.

【 授权许可】

Unknown